ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In this paper, we describe methods to exploit search queries mined from search engine query logs to improve domain detection in spoken language understanding. We propose extending...
JMLR
2010
12 years 11 months ago
2010
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
PAMI
2011
12 years 11 months ago
2011
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
JCST
2011
12 years 11 months ago
2011
Software defect detection aims to automatically identify defective software modules for efficient software test in order to improve the quality of a software system. Although many...
COLING
2010
12 years 11 months ago
2010
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
ICMCS
2009
IEEE
13 years 2 months ago
2009
IEEE
In this position paper, we first review the state-of-the-art in graph-based semi-supervised learning, and point out three limitations that are particularly relevant to multimedia ...
EMNLP
2009
13 years 2 months ago
2009
This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation class...
EMNLP
2009
13 years 2 months ago
2009
This paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. We describe an extension of semisupervised structured ...
WEBI
2010
Springer
13 years 2 months ago
2010
Springer
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
NAACL
2010
13 years 2 months ago
2010
Most learning algorithms for undirected graphical models require complete inference over at least one instance before parameter updates can be made. SampleRank is a rankbased lear...